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Abstract

The combination way of component efficiencies into the overall efficiency is a central topic in the efficiency modeling of network systems based on data envelopment analysis DEA. In terms of the feature and advantage of DEA modeling as the multiplier generation on inputs-outputs, it is desirable that the combination weights are derived from the data and self-generated in calculation process. The prior weights choice makes DEA modeling lose the objectivity and generalization in efficiency measures. This study proposes a new formulating approach of dynamic network DEA DN-DEA models to measure and decompose the overall efficiency of multi-period and -division systems without the pre-specified weights to combine component efficiencies into the overall efficiency. In our formulating approach, the double identities of carry-overs connecting consecutive periods and linkers connecting consecutive divisions are fully accounted for. This approach is applicable for the formulations of both radial measures DN-CCR and DN-BCC and non-radial measures DN-SBM. This study extends Kao’s in press relational approach of dynamic DEA to dynamic network systems for empirical comparison. In contrast to Kao’s in press approach, our approach can present a weighted average decomposition of the overall inefficiency score into components ones by a set of endogenous weight sets which are the most favorable for the tested multi-period and -division system. This makes sense of the comparison between overall and component inefficiency scores. In this context, the overall efficiency score is less or more than all component ones. We applied our models to evaluate the innovation efficiency of OECD Organization for Economic Co-operation and Development countries.



Item Type: MPRA Paper -

Original Title: Measuring and decomposing the overall efficiency of multi-period and -division systems associated with DEA-

Language: English-

Keywords: Dynamic network DEA; Multi-period and -division systems; Efficiency measurement and decomposition; Innovation efficiency; OECD countries-

Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and EstimationO - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O31 - Innovation and Invention: Processes and IncentivesP - Economic Systems > P5 - Comparative Economic Systems > P51 - Comparative Analysis of Economic Systems-





Author: Chen, Kaihua

Source: https://mpra.ub.uni-muenchen.de/55073/







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